The present invention relates to techniques for measuring the similarity among words and phrases and, in particular to techniques for generating a measure of the similarity within a keyword set for use in sponsored search advertising.
Sponsored search is an important source of revenue for providers of search services on the Web. Advertisers bid on keywords (i.e., specific words and phrases) and when those keywords are entered by users as queries into a search engine, advertisements provided by the advertisers (i.e., sponsored search results) are shown in conjunction with a list of documents and/or web pages responsive to the keywords (i.e., organic search results).
Conventionally, the keyword set for a particular advertiser is created manually by the advertiser, often according to what makes sense to individual representatives of the advertisers, possibly but not necessarily referring to some form of market research. Sometimes there might be some level of similarity among the keywords, but often the various keywords in the set might map to many different ideas and concepts.
More recently, the introduction of the notion of an ad group, i.e., an association of a particular advertisement or “creative” with a particular set of keywords, has made keyword sets that map to many concepts disadvantageous. That is, if a topically focused advertisement is invoked by the keywords in a keyword set, the advertisement is likely to be more successful to the extent that it represents the keyword(s) by which it is invoked. However, the relationship among the keywords in a keyword set relative to a particular concept are typically only evaluated in a manual and ad hoc manner.